PURPOSE. We determined the time lag between loss of retinal ganglion cell function and retinal nerve fiber layer (RNFL) thickness.METHODS. Glaucoma suspects were followed for at least four years. Patients underwent pattern electroretinography (PERG), optical coherence tomography (OCT) of the RNFL, and standard automated perimetry testing at 6-month intervals. Comparisons were made between changes in all testing modalities. To compare PERG and OCT measurements on a normalized scale, we calculated the dynamic range of PERG amplitude and RNFL thickness. The time lag between function and structure was defined as the difference in time-to-criterion loss between PERG amplitude and RNFL thickness.RESULTS. For PERG (P < 0.001) and RNFL (P ¼ 0.030), there was a statistically significant difference between the slopes corresponding to the lowest baseline PERG amplitude stratum ( 50%) and the reference stratum (>90%). Post hoc comparisons demonstrated highly significant differences between RNFL thicknesses of eyes in the stratum with most severely affected PERG ( 50%) and the two strata with least affected PERG (>70%). Estimates suggested that the PERG amplitude takes 1.9 to 2.5 years to lose 10% of its initial amplitude, whereas the RNFL thickness takes 9.9 to 10.4 years to lose 10% of its initial thickness. Thus, the time lag between PERG amplitude and RNFL thickness to lose 10% of their initial values is on the order of 8 years.CONCLUSIONS. In patients who are glaucoma suspects, PERG signal anticipates an equivalent loss of OCT signal by several years. (Invest Ophthalmol Vis Sci. 2013;54:2346-2352 DOI: 10.1167/iovs.12-11026 A n issue central to the treatment of glaucoma is determining the onset of the disease. The current understanding is that early signs of glaucoma often manifest as permanent atrophic changes in the optic nerve, which are detected by characteristic visual field defects. Structural changes can be observed directly by examining the optic nerve, but also by measuring the optic nerve and retinal nerve fiber layer (RNFL) thickness with imaging devices. It is likely that these clinically manifest structural-functional changes are preceded by subclinical stages, at which retinal ganglion cells (RGC) have lost their autoregulatory ability in response to a chronically stressful biomechanical, vascular, or molecular environment, and become increasingly dysfunctional over time until they die and are eliminated from the neuronal pool.1 The transition between normal and abnormal homeostasis may be considered the true time of disease onset, whereas the stage of RGC dysfunction preceding death represents the ideal stage during which therapeutic strategies to prevent cell death and visual loss should be initiated.The electrical responsiveness of RGC to contrast-reversing visual stimuli can be monitored noninvasively in human and experimental models of glaucoma with the pattern electroretinogram (PERG).2-7 Recent studies in human and mouse models of glaucoma have shown that in the early stages of the disease the m...

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Purpose Previous studies have shown that the onset of high-contrast, fast reversing patterned stimuli induces rapid blood flow increase in retinal vessels in association with slow changes of the steady-state PERG signal. We tested the hypothesis that adaptive PERG changes of normal controls (NC) differed from those of glaucoma suspects (GS) and patients with early manifest glaucoma (EMG). Methods Subjects were 42 GS (SAP MD −0.89 ±1.8 dB), 22 EMG (MD −2.12 ±2.4 dB) with visual acuity of ≥20/20 and 16 age-matched NC from a previous study. The PERG signal was sampled every ~15 s over 4 minutes in response to gratings (1.6 cyc/deg, 100% contrast) reversing 16.28 times/s. Amplitude/phase values of successive PERG samples were fitted with a non-parametric LOWESS smoothing function to retrieve the initial and final values and calculate their difference (delta) and the residual standard deviation around the fitted function (SDr). The magnitude of PERG adaptive change compared to random variability was calculated as log10 of percentage coefficient of variation CoV=100*SDr ÷ |delta|. Grand-average PERGs were also obtained by averaging all samples of the same series. Results The grand-average PERG amplitude (ANOVA, p=0.02), but not phase (ANOVA, p=0.63), decreased with increasing severity of disease. Adaptive changes (log10 (CoV) of PERG amplitude were not significantly associated with disease severity (ANOVA, p=0.27), but adaptive changes (log10 (CoV) of PERG phase were (ANOVA, p=0.037; linear trend, p=0.011). Conclusions The steady-state PERG signal displayed slow adaptive changes over time that could be isolated from random variability. PERG adaptive changes differed from those of grand-average PERGs (corresponding the standard steady-state PERG), thus representing a new source of biological information about retinal ganglion cell function that may have potential in the study of glaucoma and optic nerve diseases.